262 lines
8.1 KiB
Go
262 lines
8.1 KiB
Go
package newagentnode
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import (
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"context"
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"fmt"
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"strings"
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"time"
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"github.com/cloudwego/eino/schema"
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newagentllm "github.com/LoveLosita/smartflow/backend/newAgent/llm"
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newagentmodel "github.com/LoveLosita/smartflow/backend/newAgent/model"
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newagentprompt "github.com/LoveLosita/smartflow/backend/newAgent/prompt"
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newagentstream "github.com/LoveLosita/smartflow/backend/newAgent/stream"
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)
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const (
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chatStageName = "chat"
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chatStatusBlockID = "chat.status"
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chatSpeakBlockID = "chat.speak"
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)
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// ChatNodeInput 描述聊天节点单轮运行所需的最小依赖。
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//
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// 职责边界：
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// 1. 只承载"本轮 chat"需要的输入，不负责持久化；
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// 2. RuntimeState 提供 pending interaction 与流程状态；
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// 3. ConversationContext 提供历史对话；
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// 4. ConfirmAction 仅在 confirm 恢复场景下由前端传入 "accept" / "reject"。
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type ChatNodeInput struct {
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RuntimeState *newagentmodel.AgentRuntimeState
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ConversationContext *newagentmodel.ConversationContext
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UserInput string
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ConfirmAction string
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Client *newagentllm.Client
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ChunkEmitter *newagentstream.ChunkEmitter
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}
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// chatIntentDecision 是意图分类的结构化输出。
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type chatIntentDecision struct {
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Intent string `json:"intent"`
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Reply string `json:"reply,omitempty"`
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Reason string `json:"reason,omitempty"`
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}
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// Normalize 清洗意图分类结果中的字符串字段。
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func (d *chatIntentDecision) Normalize() {
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if d == nil {
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return
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}
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d.Intent = strings.TrimSpace(d.Intent)
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d.Reply = strings.TrimSpace(d.Reply)
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d.Reason = strings.TrimSpace(d.Reason)
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}
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// Validate 校验意图分类结果的最小合法性。
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func (d *chatIntentDecision) Validate() error {
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if d == nil {
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return fmt.Errorf("chat intent decision 不能为空")
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}
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d.Normalize()
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switch d.Intent {
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case "chat", "task":
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return nil
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default:
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return fmt.Errorf("未知 intent: %s", d.Intent)
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}
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}
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// RunChatNode 执行一轮聊天节点逻辑。
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//
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// 核心职责：
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// 1. 恢复判定：有 pending interaction 则处理恢复，不生成 speak；
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// 2. 意图分流：无 pending 时，调 LLM 分类 chat / task；
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// 3. 闲聊回复：纯 chat 场景直接生成回复并流式推送，phase → chatting → END；
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// 4. 任务路由：task 场景 phase → planning，交给后续 Plan 节点处理。
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//
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// 保守原则：分类失败或意图不明时，一律走 task，不丢失用户意图。
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func RunChatNode(ctx context.Context, input ChatNodeInput) error {
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runtimeState, conversationContext, emitter, err := prepareChatNodeInput(input)
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if err != nil {
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return err
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}
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// 1. 有 pending interaction → 纯状态传递，不生成 speak。
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if runtimeState.HasPendingInteraction() {
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return handleChatResume(input, runtimeState, conversationContext, emitter)
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}
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// 2. 无 pending → 调 LLM 做意图分类。
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messages := newagentprompt.BuildChatIntentMessages(conversationContext, input.UserInput)
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decision, _, err := newagentllm.GenerateJSON[chatIntentDecision](
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ctx,
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input.Client,
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messages,
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newagentllm.GenerateOptions{
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Temperature: 0.1,
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MaxTokens: 300,
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Thinking: newagentllm.ThinkingModeDisabled,
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},
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)
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if err != nil || decision.Validate() != nil {
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// 分类失败 → 保守：走 task。
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runtimeState.EnsureCommonState().Phase = newagentmodel.PhasePlanning
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return nil
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}
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// 3. 按意图分流。
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flowState := runtimeState.EnsureCommonState()
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switch decision.Intent {
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case "task":
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flowState.Phase = newagentmodel.PhasePlanning
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return nil
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case "chat":
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return handleChatReply(ctx, decision, conversationContext, emitter, flowState)
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default:
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flowState.Phase = newagentmodel.PhasePlanning
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return nil
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}
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}
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// handleChatResume 处理 pending interaction 恢复。
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//
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// 职责边界：
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// 1. 只做状态传递：吞掉用户输入、写回历史、恢复 phase；
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// 2. 不生成 speak，真正的回复由下游 Plan / Execute 节点产出；
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// 3. 只推送轻量 status 通知前端"已收到回复，正在继续"。
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func handleChatResume(
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input ChatNodeInput,
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runtimeState *newagentmodel.AgentRuntimeState,
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conversationContext *newagentmodel.ConversationContext,
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emitter *newagentstream.ChunkEmitter,
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) error {
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pending := runtimeState.PendingInteraction
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flowState := runtimeState.EnsureCommonState()
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// 把用户本轮输入写回历史（ask_user 回复、confirm 附言等）。
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if strings.TrimSpace(input.UserInput) != "" {
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conversationContext.AppendHistory(schema.UserMessage(input.UserInput))
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}
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switch pending.Type {
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case newagentmodel.PendingInteractionTypeAskUser:
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// 用户回答了问题 → 恢复 phase，交给下游节点继续。
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runtimeState.ResumeFromPending()
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_ = emitter.EmitStatus(
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chatStatusBlockID, chatStageName,
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"resumed", "收到回复，继续处理。", false,
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)
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return nil
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case newagentmodel.PendingInteractionTypeConfirm:
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return handleConfirmResume(input, runtimeState, flowState, pending, emitter)
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default:
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// connection_lost 等其他类型 → 直接恢复。
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runtimeState.ResumeFromPending()
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return nil
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}
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}
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// handleConfirmResume 处理 confirm 类型恢复。
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//
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// 分支逻辑：
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// 1. accept → 恢复后 phase 设为 executing，下游 Execute 节点接管；
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// 2. reject + 有 PendingTool（工具确认）→ 回到 executing 让 Execute 节点换策略；
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// 3. reject + 无 PendingTool（计划确认）→ 清空计划，回到 planning 重新规划。
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func handleConfirmResume(
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input ChatNodeInput,
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runtimeState *newagentmodel.AgentRuntimeState,
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flowState *newagentmodel.CommonState,
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pending *newagentmodel.PendingInteraction,
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emitter *newagentstream.ChunkEmitter,
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) error {
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action := strings.ToLower(strings.TrimSpace(input.ConfirmAction))
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switch action {
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case "accept":
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runtimeState.ResumeFromPending()
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flowState.Phase = newagentmodel.PhaseExecuting
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_ = emitter.EmitStatus(
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chatStatusBlockID, chatStageName,
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"confirmed", "已确认，开始执行。", false,
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)
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case "reject":
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runtimeState.ResumeFromPending()
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if pending.PendingTool != nil {
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// 工具确认被拒 → 回到 executing 换策略。
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flowState.Phase = newagentmodel.PhaseExecuting
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} else {
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// 计划确认被拒 → 清空计划，回到 planning。
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flowState.RejectPlan()
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}
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_ = emitter.EmitStatus(
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chatStatusBlockID, chatStageName,
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"rejected", "已取消，准备重新规划。", false,
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)
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default:
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// 无合法 confirm action → 保守：等同于 reject。
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runtimeState.ResumeFromPending()
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if pending.PendingTool != nil {
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flowState.Phase = newagentmodel.PhaseExecuting
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} else {
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flowState.RejectPlan()
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}
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}
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return nil
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}
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// handleChatReply 处理纯闲聊意图 — 把分类时产出的 reply 流式推给前端。
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func handleChatReply(
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ctx context.Context,
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decision *chatIntentDecision,
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conversationContext *newagentmodel.ConversationContext,
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emitter *newagentstream.ChunkEmitter,
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flowState *newagentmodel.CommonState,
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) error {
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reply := strings.TrimSpace(decision.Reply)
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if reply != "" {
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if err := emitter.EmitPseudoAssistantText(
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ctx, chatSpeakBlockID, chatStageName,
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reply,
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newagentstream.DefaultPseudoStreamOptions(),
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); err != nil {
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return fmt.Errorf("闲聊回复推送失败: %w", err)
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}
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conversationContext.AppendHistory(schema.AssistantMessage(reply, nil))
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}
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flowState.Phase = newagentmodel.PhaseChatting
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return nil
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}
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// prepareChatNodeInput 校验并准备聊天节点的运行态依赖。
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func prepareChatNodeInput(input ChatNodeInput) (
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*newagentmodel.AgentRuntimeState,
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*newagentmodel.ConversationContext,
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*newagentstream.ChunkEmitter,
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error,
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) {
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if input.RuntimeState == nil {
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return nil, nil, nil, fmt.Errorf("chat node: runtime state 不能为空")
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}
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if input.Client == nil {
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return nil, nil, nil, fmt.Errorf("chat node: chat client 未注入")
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}
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input.RuntimeState.EnsureCommonState()
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if input.ConversationContext == nil {
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input.ConversationContext = newagentmodel.NewConversationContext("")
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}
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if input.ChunkEmitter == nil {
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input.ChunkEmitter = newagentstream.NewChunkEmitter(
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newagentstream.NoopPayloadEmitter(), "", "", time.Now().Unix(),
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)
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}
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return input.RuntimeState, input.ConversationContext, input.ChunkEmitter, nil
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}
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